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      Genesis and spread of multiple reassortants during the 2016/2017 H5 avian influenza epidemic in Eurasia

      research-article
      a , b , c , d , e , b , d , 1 , Global Consortium for H5N8 and Related Influenza Viruses
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      Proceedings of the National Academy of Sciences of the United States of America
      National Academy of Sciences
      highly pathogenic avian influenza, emerging infectious diseases, phylogenetic analysis, poultry, wild birds

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          Significance

          In 2016/2017, highly pathogenic avian influenza (HPAI) virus of the subtype H5 spilled over into wild birds and caused the largest known HPAI epidemic in Europe, affecting poultry and wild birds. During its spread, the virus frequently exchanged genetic material (reassortment) with cocirculating low-pathogenic avian influenza viruses. To determine where and when these reassortments occurred, we analyzed Eurasian avian influenza viruses and identified a large set of H5 HPAI reassortants. We found that new genetic material likely came from wild birds across their migratory range and from domestic ducks not only in China, but also in central Europe. This knowledge is important to understand how the virus could adapt to wild birds and become established in wild bird populations.

          Abstract

          Highly pathogenic avian influenza (HPAI) viruses of the H5 A/goose/Guangdong/1/96 lineage can cause severe disease in poultry and wild birds, and occasionally in humans. In recent years, H5 HPAI viruses of this lineage infecting poultry in Asia have spilled over into wild birds and spread via bird migration to countries in Europe, Africa, and North America. In 2016/2017, this spillover resulted in the largest HPAI epidemic on record in Europe and was associated with an unusually high frequency of reassortments between H5 HPAI viruses and cocirculating low-pathogenic avian influenza viruses. Here, we show that the seven main H5 reassortant viruses had various combinations of gene segments 1, 2, 3, 5, and 6. Using detailed time-resolved phylogenetic analysis, most of these gene segments likely originated from wild birds and at dates and locations that corresponded to their hosts’ migratory cycles. However, some gene segments in two reassortant viruses likely originated from domestic anseriforms, either in spring 2016 in east China or in autumn 2016 in central Europe. Our results demonstrate that, in addition to domestic anseriforms in Asia, both migratory wild birds and domestic anseriforms in Europe are relevant sources of gene segments for recent reassortant H5 HPAI viruses. The ease with which these H5 HPAI viruses reassort, in combination with repeated spillovers of H5 HPAI viruses into wild birds, increases the risk of emergence of a reassortant virus that persists in wild bird populations yet remains highly pathogenic for poultry.

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          Most cited references46

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          Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci.

          Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set.
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            Role for migratory wild birds in the global spread of avian influenza H5N8.

            (2016)
            Avian influenza viruses affect both poultry production and public health. A subtype H5N8 (clade 2.3.4.4) virus, following an outbreak in poultry in South Korea in January 2014, rapidly spread worldwide in 2014-2015. Our analysis of H5N8 viral sequences, epidemiological investigations, waterfowl migration, and poultry trade showed that long-distance migratory birds can play a major role in the global spread of avian influenza viruses. Further, we found that the hemagglutinin of clade 2.3.4.4 virus was remarkably promiscuous, creating reassortants with multiple neuraminidase subtypes. Improving our understanding of the circumpolar circulation of avian influenza viruses in migratory waterfowl will help to provide early warning of threats from avian influenza to poultry, and potentially human, health.
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              Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010

              Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                25 August 2020
                7 August 2020
                7 August 2020
                : 117
                : 34
                : 20814-20825
                Affiliations
                [1] aThe Roslin Institute, University of Edinburgh , EH25 9RG Edinburgh, United Kingdom;
                [2] bInstitute of Diagnostic Virology, Friedrich Loeffler Institut , D-17493 Greifswald-Insel Riems, Germany;
                [3] cInstitute of Epidemiology, Friedrich Loeffler Institut , D-17493 Greifswald-Insel Riems, Germany;
                [4] dDepartment of Viroscience, Erasmus University Medical Center , 3015 NC Rotterdam, the Netherlands;
                [5] eUsher Institute, University of Edinburgh , EH9 3FL Edinburgh, United Kingdom
                Author notes
                1To whom correspondence may be addressed. Email: t.kuiken@ 123456erasmusmc.nl .

                Edited by Peter Palese, Icahn School of Medicine at Mount Sinai, New York, NY, and approved July 1, 2020 (received for review February 6, 2020)

                Author contributions: S.J.L., A.P., M.W., M.B., T.K., and G.C.f.H.a.R.I.V. designed research; S.J.L., A.P., C.S., V.C., T.K., and G.C.f.H.a.R.I.V. performed research; G.C.f.H.a.R.I.V. contributed new reagents/analytic tools; S.J.L., A.P., C.S., V.C., M.W., M.B., T.K., and G.C.f.H.a.R.I.V. analyzed data; and S.J.L., A.P., C.S., V.C., M.W., M.B., T.K., and G.C.f.H.a.R.I.V. wrote the paper.

                Author information
                https://orcid.org/0000-0003-3159-596X
                https://orcid.org/0000-0002-5318-665X
                https://orcid.org/0000-0001-5501-9049
                Article
                202001813
                10.1073/pnas.2001813117
                7456104
                32769208
                5a3349f7-6f7b-4071-bd4e-92fbbaf1669b
                Copyright © 2020 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 12
                Funding
                Funded by: EC | Horizon 2020 (EU Framework Programme for Research and Innovation) 501100007601
                Award ID: 643476
                Award Recipient : Samantha J Lycett Award Recipient : Anne Pohlmann Award Recipient : Christoph Staubach Award Recipient : Valentina Caliendo Award Recipient : Mark E J Woolhouse Award Recipient : Martin Beer Award Recipient : Thijs Kuiken
                Funded by: EC | Horizon 2020 (EU Framework Programme for Research and Innovation) 501100007601
                Award ID: 727922
                Award Recipient : Samantha J Lycett Award Recipient : Anne Pohlmann Award Recipient : Christoph Staubach Award Recipient : Valentina Caliendo Award Recipient : Mark E J Woolhouse Award Recipient : Martin Beer Award Recipient : Thijs Kuiken
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BBS/E/D/20002173
                Award Recipient : Samantha J Lycett
                Categories
                Biological Sciences
                Microbiology

                highly pathogenic avian influenza,emerging infectious diseases,phylogenetic analysis,poultry,wild birds

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